This course aims at introducing the students to econometrics, with special emphasis on time series econometrics. We will start from how to visualize the data for exploratory analysis, focusing on the identification of outliers, trends, seasonality. We next move to the analysis of the multiple regression model, covering the properties of Ordinary Least Squares estimation, and related statistics. Particular attention is given to testing for normality, homoscedasticity, auto-correlation, parameter stability, exogeneity. In the next part of the course we introduce time series analysis, discussing ARIMA models for forecasting. We next move to multi-variate forecasting using stationary variables (VARS). Finally, we introduce modern econometric techniques for time series analysis: the general-to-specific approach in model specification, cointegration using the Engle-Granger, VECM, and ADL approach. Particular attention will be given to the problem of parameter identification in structural models.
